Smartly.io's Approach to Facebook Ad Performance Optimization

We often get asked about how we do bid optimization with Facebook ads. For advertisers used to Google Adwords bidding, Facebook’s bidding options may seem complicated at first. Our approach begins with using a bid that represents the true value of a conversion to the advertiser and refraining from frequent bid manipulations, which may differ from other approaches you have seen. Read on to find out why.

Editor's note: For an updated overview of bidding, budgets & pacing on Facebook, see this blog post.

VCG in Theory – Bidding with True Values

Facebook’s ad auction is based on the Vickrey–Clarke–Groves (VCG) auction model, where a bid value should represent the true value for the auction participant. True value essentially means the maximum amount they’re willing to pay. That is how every auction participant's profit is theoretically maximized in single auctions or in cases with unlimited budgets. Auction participants do not stand to gain from bidding above or below their true value, because higher bids can result in paying more than the true value, while lower bids can lead to profitable opportunities being missed.

Pacing – Taking Budget Constraints Into Consideration

The Facebook ad delivery system’s built-in pacing then takes budget constraints into account, essentially modifying the true value bids used in the ad auctions. When an ad set’s budget is limiting delivery, the bid values are adjusted in auctions so that the advertiser only competes for the impressions with the highest estimated value-price ratios. You can read more about pacing in our earlier blog post.

So, in theory, an advertiser on Facebook maximizes their profit with a bid and a budget that represent their true value for one action and their true budget constraint. But this only applies when the advertiser has just a single ad set.

Predictive Budget Allocation – Managing Budget Constraints

With multiple ad sets, the challenge becomes that some are more profitable than others. In this situation our Predictive Budget Allocation is useful, automatically managing budget constraints between ad sets – within an individual campaign or across multiple campaigns – so that budgets are taken from the less profitable ad sets and moved to those with the highest expected return-on-ad-spend (ROAS) (and for which the budget is limiting delivery).

Predictive Budget Allocation explained in 1 minute

Facebook's Bidding Optimization – Avoiding Arbitrary Bid Limitations

We mentioned above that pacing uses budget constraints to adjust the true value bids used in ad auctions. There are however many other things that affect the true value bid used in ad auctions.

Since the introduction of oCPM bidding back in 2012, Facebook has worked to better leverage past conversion data together with the vast amount of data they have on their users. This helps Facebook’s bid optimization to deliver ads to the right people for the ad set’s optimization goal. Based on characteristics, past behaviour, and similarity to recently converting users, it’s able to decide which specific Facebook users warrant a higher bid for ad impressions.

Because Facebook's ad delivery optimization leverages a vast amount of proprietary user data, it's better for advertisers to give the oCPM bidding algorithm enough room to make its own bid adjustment decisions by bidding the true value.

Because Facebook's ad delivery optimization leverages a vast amount of proprietary user data, it's better for advertisers to give the oCPM bidding algorithm enough room to make its own bid adjustment decisions by bidding the true value. Bidding less would mean missing valuable opportunities to win auctions for the people most likely to take the action you want.